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Client-Side Defense Against Web-Based Identity Theft

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Client-Side Defense Against Web-Based Identity Theft Client-side defense against web-based identity theft Neil Chou Robert Ledesma Yuka Teraguchi Dan Boneh John C. Mitchell Computer Science Department, Stanford University, Stanford CA 94305 {neilchou, led242, yukat, dabo, jcm}@stanford.edu Abstract experiment with this approach using a browser plug-in called SpoofGuard. The plug-in monitors a user’s In- ternet activity, computes a spoof index, and warns the Web spoofing is a significant problem involving fraud- user if the index exceeds a level selected by the user. ulent email and web sites that trick unsuspecting users While Internet-savvy users who watch the address bar, into revealing private information. We discuss some status bar, and other information carefully may not need aspects of common attacks and propose a framework SpoofGuard, the current level of accuracy and effec- for client-side defense: a browser plug-in that exam- tiveness may be sufficient to help many unsophisticated ines web pages and warns the user when requests for web users. If the methods we propose become widely data may be part of a spoof attack. While the plug- deployed, through our plug-in or through other client- in, SpoofGuard, has been tested using actual sites ob- side defensive software, then phishers will certainly take tained through government agencies concerned about steps to circumvent them. However, we expect further the problem, we expect that web spoofing and other effort and study to produce correspondingly better de- forms of identity theft will be continuing problems in fenses. Moreover, if synergistic server-side methods are coming years. deployed by concerned companies, it seems possible to thwart increasingly sophisticated attacks. SpoofGuard uses domain name, url, link, and 1 Introduction image checks to evaluate the likelihood that a given page is part of a spoof attack. For ex- Web spoofing, also known as “phishing” or “carding” ample, a page with a suspicious url such as [CNN03, FBI03], is a significant form of Internet crime etrade-maintenance.suspicious.org that is launched against hundreds or thousands of indi- or [email protected]/ viduals each day. The US Secret Service and the San maintainance.asp and an E*Trade logo will have Francisco Electronic Crimes Task Force report that ap- a higher spoof index than a page with neither of these proximately 30 attack sites are detected each day. Each characteristics. SpoofGuard also uses history, such as attack site may be used to defraud hundreds or thousands whether the user has visited this domain before and of victims, and it is likely that many attack sites are whether the referring page was from an email site never detected. A typical web spoof attack begins with such as Hotmail or Yahoo!Mail. Most importantly, bulk email to a group of unsuspecting victims. Each is SpoofGuard intercepts and evaluates user posts in told that there is a problem with their account at a site light of relevant history and the spoof index of a form such as E*Trade. Victims of the spoofing attack then fol- page. SpoofGuard examines post data user name and low a link in the email message to connect to a spoofed password fields and compares posted data to previ- E*Trade site. Once a victim enters his or her user name ously entered passwords from different domains. This and password on the spoof site, the criminal has the mechanism warns a user against sending her E*Trade means to impersonate the victim, potentially withdraw- password to a site with an E*Trade logo but outside ing money from the victim’s account or causing harm in the etrade.com domain, for example. Password other ways. comparisons are done using a cryptographically secure We describe some common characteristics of recent hash, so that plaintext passwords are never stored by web spoofing attacks and propose a framework for SpoofGuard. client-side countermeasures. Like other inexact detec- Stopping web spoofing bears some similarity to intru- tion mechanisms, including virus detection and email sion detection, spam filtering, and thwarting traditional spam filtering, the approach we explore involves look- social engineering attacks. Intrusion detection systems ing for characteristics of previously detected attacks. We [Pax99, Sno03] typically monitor network and host ac- 1 tivity, compute statistical or other indices, and attempt tegrity of browser indicators such as the url indicator in to detect intrusions by comparing the index of current the status bar, not analyzing user behavior, web pages, activity against previous statistics. While web spoofing and html post data to stop leakage of sensitive user in- may be regarded as a special case of intrusion detection, formation. While we considered using an alternate term the browser seems like that appropriate place to combat such as “phishing” in this paper, we use “web spoofing” web spoofing. A browser plug-in is relatively easy to in- since this currently appears to be the term most com- stall and has access to honest and spoof pages sent over monly used by law enforcement and concerned compa- https, giving SpoofGuard a better chance of catching an nies. attack than a network proxy or other external http traffic The goals of this paper are to raise awareness of the monitors. While a plug-in alone does not have full infor- web spoofing problem and propose a framework for mation from email programs such as Outlook or Eudora client-side protection. While sophisticated and deter- that may contain the messages that launch an attack, the mined attackers will be able to circumvent our current browser does provide an indication of the referring page tests (through simple techniques we explain later in the or application, and it is possible to scan and parse pages paper), there is plenty of room for improving specific from email sites such as Hotmail or Yahoo!Mail. There- tests and tuning the coefficients of our spoof index func- fore, for non-expert users who read email through their tion. Furthermore, the web spoofing problem is impor- browser, SpoofGuard has the potential to examine every tant and we believe our SpoofGuard experience will be step of a standard web spoof attack. useful for developing more sophisticated defenses. We Like other intrusion detection efforts, it is appropriate discuss the web spoofing problem in more detail in Sec- to evaluate SpoofGuard by measuring its effective at pre- tion 2, and our solutions in Section 3. The SpoofGuard venting attacks, the false alarm rate (number of unnec- implementation and user interface are described in Sec- essary warnings), and its performance impact. Spoof- tion 4. Some SpoofGuard evaluation information ap- Guard will only be useful if it detects attacks without pears in Section 5, followed by suggestions for server- raising too many false alarms, since users will almost side methods in Section 6, some more speculative client- certainly reject any method that interferes with normal side methods in Section 7, and concluding remarks in browsing activity. We have evaluated the false-alarm Section 8. rate by using SpoofGuard ourselves over a period of Throughout the paper we use the following terminol- time, and we have evaluated its effectiveness for pre- ogy. venting attacks using actual spoof sites brought to our • Spoof site or Spoof page: the site or page that is a attention by members of the San Francisco Electronic malicious copy of some legitimate web page. Crimes Task Force. While this is not an extensive • Attacker: the person or organization who sets up enough test to draw broader conclusions, SpoofGuard the spoof site. does catch the sample attacks found in the wild and does • Honest site or honest page: the legitimate site or not add any noticeable delay to ordinary web browsing. page that is being spoofed. Since web spoofing attacks begin with bulk email, a • Spoof index: a measure of the likelihood that a spe- good general spam solution [Bri03, Din03] could reduce cific page is part of a spoof attack, described in Sec- the incidence of web spoofing attacks. However, current tion 3. spam solutions are only partly effective at blocking un- wanted email, and we are not aware of any spam efforts A prototype version of SpoofGuard will be made pub- aimed specifically at identify theft. While the browser- licly available shortly. based techniques we explore in this paper are comple- mentary and independent of spam filtering, there may be 2 Theproblem additional ways of combining email scanning with web According to Agents of the U.S. Secret Service San page analysis that will lead to better spoof prevention in Francisco Electronic Crimes Task Force [Von03], the the future. U.S. Government’s Internet Fraud Complaint Center re- Previous efforts by the Princeton Secure Internet Pro- ceived over 75,000 complaints in 2002. Of this number, gramming group and others [FBDW97, EY01] have ad- 48,000 cases resulted in further action requests. This is dressed another form of “web spoofing” in which an a three-fold increase over 2001. The total dollar losses attacker causes all html page requests from a victim are estimated at more than $54 million compared to $17 to pass through the attacker’s site. This form of web million for 2001. A majority of these fraud complaints spoofing allows the attacker to monitor all of the vic- are intrusions, auction fraud, credit card/debit fraud, and tim’s activities, including posted passwords or account computer intrusion. Agents of the U.S. Secret Service numbers. However, previous methods for countering San Francisco Electronic Crimes Task Force report that this form of attack have focused on maintaining the in- web spoofing was first noticed in late 2001 and grew in 2 popularity in 2002, correlating with the large increase in gan Stanley’s Discover unit, eBay Inc.
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